R Markdown

This project was created as part of the Developing Data Products course of the Coursera Data Science Specialisation.

The goal of the project is to create a web page presentation using R Markdown that features a plot created with Plotly, and to host the resulting web page on either GitHub Pages, RPubs, or NeoCities.

The interactive plot on the next slide represents the number of road accidents in Great Britain from 2005 to 2015, grouped by severity (slight, serious, or fatal).

A Loess smoother line has been added to highlight the overall evolution of the number of accidents.

rm(list=ls())

library(plotly)
## Loading required package: ggplot2
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
library(data.table)

library(tidyr)

library(lubridate)
## 
## Attaching package: 'lubridate'
## The following objects are masked from 'package:data.table':
## 
##     hour, isoweek, mday, minute, month, quarter, second, wday,
##     week, yday, year
## The following object is masked from 'package:base':
## 
##     date
library(zoo)
## 
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

Data Loading

The source data sets are not included in this repository. the zip files in a subdirectory named data.

accidents0514 <- fread("data/dftRoadSafety_Accidents_2016.csv", header = TRUE, sep = ",")
accidents0514 <- accidents0514 %>%
select(Accident_Severity, Date)
accidents15 <- fread("data/dftRoadSafety_Accidents_2017.csv", header = TRUE, sep = ",")
accidents15 <- accidents15 %>%
select(Accident_Severity, Date)

#concatenate data tables and free up environment
accidents <- rbind(accidents0514, accidents15)
rm(list = c("accidents0514", "accidents15"))

Processing Data

# convert severity to factor and add labels

accidents$Accident_Severity <- 

  factor(accidents$Accident_Severity, 

         levels = 1:3, labels = c("Fatal", "Serious", "Slight"))



# convert date strings to Date objects

accidents$Date <- dmy(accidents$Date)



# group data by date and severity, get count, one row per date

accident_count <- accidents %>% 

  group_by(Date, Accident_Severity) %>%

  summarise(count = n()) %>%

  spread(key = Accident_Severity, value = count) %>% 

  as.data.frame()



# create a smoother for each severity to visualise general trends

loess_slight <- loess(Slight ~ as.numeric(Date), 

                      data = accident_count)

loess_serious <- loess(Serious ~ as.numeric(Date), 

                       data = accident_count)

loess_fatal <- loess(Fatal ~ as.numeric(Date), 

                     data = accident_count)

Road accidents in GB (2005-2015)

# plot data

plot_ly(accident_count) %>%

  add_trace(x = ~Date, y = ~Slight, type="scatter", mode = "markers", 

            name = "slight", legendgroup = "slight", 

            marker = list(color = "#52A9BD")) %>%

  add_trace(x = ~Date, y = ~Serious, type="scatter", mode = "markers",

            name = "serious", legendgroup = "serious", 

            marker = list(color = "#FFF16B")) %>%

  add_trace(x = ~Date, y = ~Fatal, type="scatter", mode = "markers",

            name = "fatal", legendgroup = "fatal", 

            marker = list(color = "#F5677D")) %>%

  add_trace(x = as.Date(loess_slight$x), y = fitted(loess_slight),

            type="scatter", mode = "lines",

            line = list(color = '#1A7A90'), 

            name = "slight Loess smoother", legendgroup = "slight", 

            hoverinfo = 'none', showlegend = FALSE) %>%

  add_trace(x = as.Date(loess_serious$x), y = fitted(loess_serious),

            type="scatter", mode = "lines",

            line = list(color = '#E9D625'),

            name = "serious Loess smoother", legendgroup = "serious",

            hoverinfo = 'none', showlegend = FALSE) %>%

  add_lines(x = as.Date(loess_fatal$x), y = fitted(loess_fatal),

            type="scatter", mode = "lines",

            line = list(color = '#DC2340'),

            name = "fatal Loess smoother", legendgroup = "fatal",

            hoverinfo = 'none', showlegend = FALSE) %>%

  layout(

    xaxis = list(title = "date"),

    yaxis = list(title = "number of accidents")

  )
## Warning: Ignoring 17 observations